Tale of two finance departments

| June 28, 2016

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Concur surveyed members of the Institute of Chartered Accountants in England and Wales (ICAEW) about their use of financial technology. Based on the results, it seems that there are two kinds of finance departments in the UK: those who are leading the financial technology charge and others who are struggling to keep up.

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Five Application Scenarios of AI in Banking

Article | April 13, 2021

Over the past decades, banks have been improving their ways of interacting with customers. They have tailored modern technology to the specific character of their work. For example, in the 1960s, the first ATMs appeared, and ten years later, there were already cards for payment. At the beginning of our century, users learned about round-the-clock online banking, and in 2010, they heard about mobile banking. But the development of the financial system didn’t stop there, as the digital age is opening up new opportunities — the use of Artificial Intelligence. By 2023, banks are projected to save $447 billion by applying AI apps. We will tell you how financial institutions are making use of this technology in their operations today. AI-powered chatbots Chatbots are AI-enabled conversational interfaces. This is one of the most popular cases of applying AI in banking. Bots communicate with thousands of customers on behalf of the bank without requiring large expenses. Researchers have estimated that financial institutions save four minutes for each communication that the chatbot handles. Since customers use mobile apps to carry out monetary transactions, banks embed chatbot services in them. This makes it possible to attract users’ attention and create a brand that is recognizable in the market. For example, Bank of America launched a chatbot that sends users notifications, informs them about their balances, makes recommendations for saving money, provides updates to credit reports, and so on. This is the way the bank helps its clients to make informed decisions. Another example is the launch of the Ceba chatbot, which brought great success to the Australian Commonwealth Bank. With its help, about half a million customers were able to solve more than two hundred banking issues: activate their cards, check account balances, withdraw cash, etc. Mobile banking AI functionality in mobile apps is becoming more proactive, personalized, and advanced. For example, Royal Bank of Canada has included Siri in its iOS app. Now, to send money to another card, it’s enough to say something like: "Hey, Siri, send $30 to Lisa!" - and confirm the transaction using Touch ID. Thanks to AI, banks generate 66% more revenue from mobile banking users than when customers visit branches. Banking organizations are paying close attention to this technology to improve their quality of services and remain competitive in the market. Data collection and analysis Banking institutions record millions of business transactions every day. The volume of information generated by banks is enormous, so its collection and registration turn into an overwhelming task for employees. Structuring and recording this data is impossible until there is a plan for its use. Therefore, determining the relationship between the collected data is challenging, especially when a bank has thousands of clients. There used to be the following approach: a client came to a meeting with a bank employee who knew their name and financial history and understood what options were better to offer. But that's history now. With the wealth of data coming from countless transactions, banks are trying to implement innovative business ideas and risk management solutions. AI-based apps collect and analyze data. This improves the user experience. The information can be used for granting loans or detecting fraud. Companies that estimated their profit from Big Data analysis have reported an average increase in revenue by 8% and a reduction in costs by 10%. Risk management Extension of credit is quite a challenging task for bankers. If a bank gives money to insolvent customers, it can get into difficulties. If a borrower loses a stable income, this leads to default. According to statistics, in 2020, credit card delinquencies in the U.S. rose by 1.4% within six months. AI-powered systems can appraise customer credit histories more accurately to avoid this level of default. Mobile banking apps track financial transactions and analyze user data. This helps banks anticipate the risks associated with issuing loans, such as customer insolvency or the threat of fraud. Data security According to the Federal Trade Commission report for 2020, credit card fraud is the most common type of personal data theft. AI-based systems are effective against malefactors. The programs analyze customer behavior, location, and financial habits and trigger a security mechanism if they detect any unusual activity. ABI Research estimates that spending on AI and cybersecurity analytics will amount to $96 billion by the end of 2021. Amazon has already acquired harvest.AI - an AI cyber security startup - and launched Macie - a service that applies Machine Learning to detect, sort, and structure data in S3 cloud storage.

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Are banks ready for the Corona emergency measures imposed by governments?

Article | March 26, 2020

Amid the Corona crisis, governments worldwide are urgently deciding on numerous actions to limit the economic impact of this unprecedented health crisis. Top priority in these plans is to help people and businesses overcome a period of low to zero income, which completely breaks their predicted liquidity forecasts. Such a shock in liquidity can even bring strong businesses on their knees, if no supporting measures are put in place.

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Insights from the Ground: Managing Through the COVID-19 Pandemic

Article | July 16, 2020

In this series, we share insights from our Citi Country Officers (CCOs) around the globe as they reflect on their experiences during COVID-19. CCOs are responsible for leading the entire Citi franchise in their country. They provide alignment and leadership to bring our global strategy to life in each of their jurisdictions. For us at Citi in Italy we prepared for the COVID pandemic in a number of different ways. First, we leveraged lessons learned from our colleagues in the countries that were hit before us, including China and Korea, even if their context was quite different from the European one.

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Natural Language Processing Applications in Finance – 3 Current Applications

Article | February 26, 2020

Natural language processing, (NLP) is one AI technique that’s finding its way into a variety of verticals, but the finance industry is among the most interested in the business applications of NLP. In fact, according to our AI Opportunity Landscape research in banking, approximately 39% of the AI vendors in the banking industry offer solutions that involve NLP.

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Spotlight

PMI Health Group

"Willis PMI Group is one of the UK’s largest providers of employee healthcare and risk management services. We’re here to help you and your staff stay fit for business. We offer a unique combination of in-house medical and insurance expertise. In fact, almost one in five of our client-facing staff is medically trained, giving you the convenience of one port of call for all your employee healthcare needs...

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